8 BED-CEIA % characterized as “recent” Duration of infection (years)The probability of testing recently infected by time from seroconversion is fitted with a cubic splineThe area under the modeled probability curve using numerical integration provided the window period% characterized as “recent”BED-CEIA: Does not converge to zeroCannot determine window period(average time classified as recently infected)20% % % % %Duration of infection (years)

9 BED-CEIA vs. Multi Assay AlgorithmThe probability of testing recently infected by time from seroconversion is fitted with a quadratic splineThe area under the modeled probability curve using numerical integration provided the window period% characterized as “recent”BED-CEIA: Does not converge to zeroCannot determine window period(average time classified as recently infected)20% % % % %Multi-assay algorithm : Does converge to zeroWindow period: 141 days (95% CI: days)BEDMAADuration of infection (years)

11 SummaryThe multi-assay algorithm has a window period of 141 days with no misclassification of individuals infected 4+ yearsIncidence estimates obtained using the multi-assay algorithm are nearly identical to estimates based on HIV seroconversionWe are now determining the optimal cut-off values for the multi-assay algorithm

15 Comparison of cross-sectional incidence testing to known incidenceLongitudinal cohortPerform cross-sectionalincidence testingSurvey rounds1234Compare the incidence estimate based on HIV seroconversion to the estimate based on cross-sectional testing using the multi-assay algorithmHIV incidence between survey rounds (HIV seroconversion)HIV-HIV+